Starting Fever and Its Relationship with 50m Freestyle Swimming in Youth

The research aimed at identifying the relationship between starting fever and 50m freestyle achievement in youth swimmers by measuring this type of anxiety as a psychological variable and its relationship with achievement as a physical variable. The researchers used the descriptive method on (10) swimmers from Baghdad clubs while the pilot study was conducted on (4) swimmers. They used a starting fever scale in the form of a questionnaire presented to the subjects before an hour from the race. The data was collected and treated using proper statistical operations to conclude a relationship between start fever and 50m freestyle achievement in youth swimmers. Finally, the researchers recommended paying more attention to start fever due to its great importance in 50m freestyle achievement as well as making similar studies on other activities that require speed performance and achievement of swimmers.

A Computational Model of Human Perception With Prior Expectation: Bayesian Integration and Efficient Coding

Human perception of sensory stimuli is affected by prior prediction of the sensory experience. For example, perception of weight of an object changes depending on weight predicted with size of the object appearance. We call such psychological phenomena expectation effect. The expectation effect is a key factor to explain a gap between physical variables and their perceptions. In this paper, we propose a novel computational model of human perception involving the expectation effect. We hypothesized that perceived physical variable was estimated using a Bayesian integration of prior prediction and sensory likelihood of a physical variable. We applied efficient coding hypothesis to form a shape of sensory likelihood. We formalized the expectation effect as a function of three factors: expectation error (difference between predicted and actual physical variables), prediction uncertainty (variance of prior distributions), and external noise (variance of noise distributions convolved with likelihood). Using the model, we conducted computer simulations to analyze the behavior of two opposite patterns of expectation effect, that is, assimilation and contrast. The results of the simulation revealed that 1) the pattern of expectation effect shifted from assimilation to contrast as the prediction error increased, 2) uncertainty decreased the extent of the expectation effect, 3) and external noise increased the assimilation.

Myoelectric Control of Prosthetic Devices for Rehabilitation

Bio-signals patterns analysis problems have enjoyed a rapid increase in popularity in the past few years. The electromyography (EMG) signal, also referred to as the Myoelectric signal (MES), recorded at the surface of the skin, is one of the biosignals generated by the human body, representing a collection of electrical signals from the muscle fibre, acting as a physical variable of interest since it first appeared in the 1940s (Scott, 1984). It was considered to be the main focus of scientists, and was advanced as a natural approach for the control of prosthesis, since it is utilising the electrical action potential of the residual limb’s muscles remaining in the amputee’s stump (which still has normal innervations, and thus is subject to voluntary control) as a control signal to the prosthesis—in other words, it allows amputees to use the same mental process to control their prosthesis as they had used in controlling their physiological parts; however, the technology in that time was not adequate to make clinical application viable. With the development of semiconductor devices technology, and the associated decrease in device size and power requirements, the clinical applications saw promise, and research and development increased dramatically.